Open AccessBlood Supply Chain Risk Management using House of Risk Model
Author(s) -
Wijai BOONYANUSITH,
Phongchai JITTAMAI
Publication year - 2018
Publication title -
walailak journal of science and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.146
H-Index - 15
eISSN - 2228-835X
pISSN - 1686-3933
DOI - 10.48048/wjst.2019.3472
Subject(s) - supply chain risk management , supply chain , risk management , risk analysis (engineering) , supply chain management , business , information sharing , risk assessment , service management , operations management , process management , computer science , marketing , finance , computer security , engineering , world wide web
Managing blood supply chain has been an important task in the healthcare system because it has to confront not only blood demand and supply uncertainties but also complexities in blood inventory management. In order to overcome these challenges, it is essential to explore the possible risks that could occur in the blood supply chain and discover proper ways to manage these risks. Therefore, this research aims to investigate risks in blood supply chain by using a proactive risk management tool called ‘house of risk’ (HOR) model, in order to conduct risk assessment and evaluate risk management actions. A case study of blood supply chain risk management was analyzed, and the HOR model was incorporated to appraise the appropriate actions in the real situation. The results indicate that there are 30 risk events and 16 risk agents identified and assessed in the case study. The outcomes point out that lack of collaboration, insufficient information for decision-making, and limited information sharing are the top 3 risk agents that contribute to significant impact on blood supply chain management. Risk mitigation and management actions were evaluated and the results show that enhancing the collaboration is the most proactive action to manage risks in the blood service operations, followed by information sharing, and demand and supply statistical analysis. The study has recommended the outlines for improving collaboration between blood service organizations by using information system and technology to mitigate risks, complexities, as well as uncertainties in managing demand and supply in the blood supply chain.